toon

Encode JSON into compact TOON format for reduced token usage.

27|9|Updated Jan 4, 2026
One-click install
npx skills add https://github.com/georgekhananaev/claude-skills-vault --skill toon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: toon
Source: https://github.com/georgekhananaev/claude-skills-vault/tree/main/.claude/skills/document-skills/toon
Command: npx skills add https://github.com/georgekhananaev/claude-skills-vault --skill toon

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @toon-format/toon, and includes scripts (resource) components.

What problem does it solve?

TOON provides a compact, human-readable encoding of JSON designed to minimize token usage in LLM prompts while preserving lossless round-trips.

Core Features & Use Cases

  • Compact data encoding: reduces token counts for large JSON payloads without losing structure.
  • Uniform arrays and object representations: supports tabular-style arrays for efficient parsing by LLMs.
  • Use Case: quickly convert API responses or configuration payloads into TOON to speed up prompt processing and improve comprehension.

Quick Start

Convert a sample.json to TOON using the Node.js converter: node convert.js sample.json > sample.toon. Then decode back with --verify to ensure round-trip integrity.

Frequently Asked Questions about toon

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compress JSON to reduce token usage in LLM prompts?▼

You can compress JSON for LLM prompts by converting it into the TOON format, a compact, human-readable encoding that minimizes token counts while preserving lossless round-trips. It efficiently reduces large data payloads without losing structure.

What is the best way to convert large API responses for LLM processing?▼

The best way to convert large API responses is encoding them as TOON, which transforms heavy JSON payloads into a compact, tabular-style format. This speeds up prompt processing and improves LLM comprehension of configuration data.

How do I encode JSON files using Node.js for compact data storage?▼

To encode JSON files using Node.js, run the converter script: `node convert.js sample.json > sample.toon`. This requires the @toon-format/toon library and outputs a compact, human-readable format optimized for LLMs.

Does TOON support lossless round-trips from JSON to compact text and back?▼

Yes, TOON supports lossless round-trips between JSON and its compact format. You can decode the output back to JSON and verify integrity using the `--verify` flag to ensure no data is lost during conversion.

Can I use Python to encode and decode JSON payloads if Node.js is unavailable?▼

Yes, you can use a Python fallback to encode and decode JSON payloads if Node.js is unavailable. The TOON format supports both the @toon-format/toon Node library and a Python alternative for data conversion.

When should I not use compact JSON encoding for LLM workflows?▼

You should avoid compact JSON encoding for workflows that do not involve data-heavy payloads or large datasets. If prompt length is not a constraint, standard JSON may be sufficient without requiring format conversion.